MétaCan
Menu
← Back to cohort
Record W4403831963 · doi:10.1681/asn.2024pnzjpnze

Impact of Diabetes on Physical Function Recovery following Kidney Transplantation

2024· article· en· W4403831963 on OpenAlexaff
Jad Fadlallah, Eliana Barbuzzi, Fabiha Razzak, Caroline Carruthers, C Commisso, Nishat Fatima Syeda, Nathaniel Edwards, Heather Ford, István Mucsi

Bibliographic record

VenueJournal of the American Society of Nephrology · 2024
Typearticle
Languageen
FieldMedicine
TopicDialysis and Renal Disease Management
Canadian institutionsUniversity Health Network
Fundersnot available
KeywordsMedicineDiabetes mellitusKidney transplantationTransplantationRenal functionUrologyIntensive care medicineInternal medicineEndocrinology

Abstract

fetched live from OpenAlex

Background: Diabetes mellitus (DM) can impair post-operative recovery. We assess the association of DM with recovery of physical function over time among incident kidney transplant (KT) recipients using the Patient Reported Outcome Measurement Information System (PROMIS) physical function computer adaptive test (PF-CAT). Methods: Longitudinal convenience sample of incident (<30 days post-transplant) adult KT recipients recruited in 2021-2024. Demographic information was self-reported, clinical data extracted from health records. Participants completed PROMIS PF-CAT at baseline, biweekly for 3 months, and then every four weeks up to 6 months on an electronic data capture platform. PROMIS PF-CAT is scored on a T-score metric (20-80, higher scores=better physical function). Linear mixed-effect models with random intercepts were used to compare PF recovery between DM and non-DM (NDM) KT recipients. The model included the interaction between time and diabetes status, representing the average difference in PF over time, adjusting for age, sex, education, socioeconomic status, BMI and significant anxiety or depression symptoms at baseline. Individual clinically significant improvement in PF was assessed in a time-to-event analysis, with the use of log-rank tests and Cox proportional-hazards model adjusting for mentioned covariates. The primary event was defined as reaching a T-score ≥50. Results: Of 110 participants, 71(65%) were male, 62(56%) were white, 36(33%) had DM, mean(SD) age was 51(15) years and median[IQR] time since transplantation at enrollment was 4[3; 7] days. DM had significantly lower PROMIS PF over time (ref:NDM, coeff, -0.19; 95%CI, -0.33 to -0.05). At baseline, mean(SD) scores in DM(n=36) vs NDM(n=74) were 39(10) vs 39(8). At 12w, scores in DM(n=11) vs NDM(n=33) were 45(6) vs 47(6). At 24w, scores in DM(n=11) vs NDM(n=30) were 48(5) vs 51(6). The cumulative incidence of the event was 25 in NDM vs 5 in DM, p=0.02. This association remained significant after adjusting for covariates (ref: NDM, HR, 0.33; 95%CI 0.11 to 0.95, p=0.04). Conclusion: KT recipients with DM demonstrated less significant improvements in PF over 6 months compared to NDM. KT with DM may need extra support for their PF, such as prehabilitation or post-transplant rehabilitation. Funding: Private Foundation Support, Government Support – Non-U.S.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.008
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.003
Threshold uncertainty score0.014

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0000.001
Science and technology studies0.0000.000
Scholarly communication0.0010.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0020.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.010
GPT teacher head0.285
Teacher spread0.275 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2024
Admission routes1
Has abstractyes

Explore more

Same venueJournal of the American Society of Nephrology→Same topicDialysis and Renal Disease Management→French-language works237,207→